DFG: Machine Learning in Chemical Engineering. Knowledge Meets Data: Interpretability, Extrapolation, Reliability, Trust

Freitag, 24. Juli 2020 um 10:43 Uhr

The present call invites tandem proposals for the first three-year funding period. Each proposal must operate at the interface of CE and ML and have at least two applicants with corresponding expertise. The projects shall consider at least one of six areas:

  1. optimal decision making,
  2. introducing/enforcing physical laws in ML models,
  3. heterogeneity of data,
  4. information and knowledge representation,
  5. safety and trust in ML applications, and
  6. creativity.

The projects are expected to open up new methods for CE, formulate new types of problems for ML, and jointly generate advances for methods in both ML and CE.

Proposals must be written in English and submitted to the DFG by 19 January 2021 via elan, the DFG’s electronic proposal processing system.

Weitere Informationen:

https://www.dfg.de/foerderung/info_wissenschaft/info_wissenschaft_20_42/index.html

http://www.chemengml.org/